Exploring Learner Acceptance of Text-to-Image AI in e-Learning

• In Event: Virtual Poster Session
  In Virtual iPresentation Only: Division I - Education in the Professions Virtual Poster Session

Abstract

This study examines the integration of Text-to-Image AI technology in online medical education and its impact on learner acceptance, using the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. A total of 175 medical students participated in the survey and the research identifies key factors influencing technology acceptance. Quantitative analysis reveals strong positive correlations between predictive factors and acceptance, while ethical concerns significantly affect acceptance levels. Qualitative insights highlight enhanced learning experiences, concerns about AI bias, and the importance of ethical guidelines. The findings suggest that addressing usability and ethical issues is crucial for the successful integration of AI technologies in online medical education.

Authors

• Henry Moon, Augusta University

• Anusha Aiyar, Medical College of Georgia